A Method of Fiber Bragg Grating Sensing Signal De-Noise Based on Compressive Sensing
作者： Yong Chen , Zhiqiang Liu , Huanlin Liu
DOI: 10.1109/ACCESS.2018.2819647
关键词: Interference (wave propagation) 、 Signal 、 Interference (communication) 、 Wavelet 、 Compressed sensing 、 Noise reduction 、 Computer science 、 Fiber Bragg grating 、 Algorithm 、 Reconstruction algorithm 、 Hilbert–Huang transform
摘要: A novel de-noising method based on the compressive sensing reconstruction algorithm is proposed in this paper, which used to solve problem that fiber Bragg grating (FBG) signal easily affected by environment interference. By analyzing characteristics of FBG sparse domain, we calculated sparsity through exponential fitting method. Considering complexity traditional algorithm, a reasonable threshold for selecting multi-atom reduce run time algorithm. In addition, designed elimination strategy and double termination conditions improve precision reconstructed signal. The experiment results show maximum signal-to-noise ratio our 49.2 dB, with relative error 0.0034~0.0074. much lower than same-type algorithms. far beyond wavelet empirical mode decomposition.
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